While interconnected, Machine Learning, Data Science, and Artificial Intelligence are still significantly different from one another. A Data Scientist or a Data Analyst needs to be adept at each of these skills, there is also a need to learn how they are similar and how they are unique from one another. Here’s delving deep into it.
What is Data Science?
Data Science is an interdisciplinary field that relies on studying large data sets and interpreting them to extract valuable information. Data Scientists use statistical methods, algorithms, and scientific computing, to extract that information from complex data sets and draw a pattern to find the solution. They also often solve complex problems and make bold predictions, based on business needs.
What is Artificial Intelligence?
Artificial Intelligence is a subset of Computer Science that allows machines to perform tasks on its own that require human intelligence. AI, if and when trained well, can simulate learning, researching, thinking, problem solving, decision making, and many more such things. From diagnosing patients to creating intelligent machines to coming up with creative solutions to self-driving cars and visual assistants, AI has found its foothold everywhere. You can also use it for entertainment purposes like enhancing videogames or configuring computers to play them by themselves.
AI works in a five-pronged method – Natural Language Processing, Deep Learning, Neural Networks, Reinforcement Learning, and Machine Learning. Each of these methods either involves reading data or analyzing algorithms to come up with a solution.
What is Machine Learning?
Machine Learning is a subset of Artificial Intelligence that allows computers to learn from data without explicit programming. This helps the AI to improve its performance and start making predictions or make decisions over time. It mainly focuses on building platforms and systems that enable computers or machines to learn from data.
Since Machine Learning helps improve performance without being explicitly programmed, it involves deep algorithms that help identify patterns, make predictions, and learn from experience. It is a must-learn for all Data Scientists and Data Analysts.
Difference Between AI, ML, and Data Science
Artificial Intelligence is the broadest field of them all, with enormous goals such as creation of intelligent machines and self-driving cars, among others. Machine Learning is a subset of AI that focuses on algorithms and doesn’t rely on programming. Whereas, Data Science is an interdisciplinary field of study that utilizes various techniques, including Machine Learning, to study large data sets, extract information, and come up with solutions.
It is interdisciplinary since it involves knowledge about statistical analysis, scientific methods, processes and algorithms. Here’s a more detailed look at Machine Learning vs. Data Science vs. Artificial Intelligence:
- AI encompasses a wide range of approaches, including Machine Learning, and Natural Language Processes, and Expert Systems. Machine Learning, a subset of AI, only works with developing algorithms that can identify patterns and make predictions. Data Science involves cleaning, collecting, analyzing, and interpreting data to derive valuable insights from it.
- The ultimate goal of AI is to create a system that can mimic human intelligence and perform tasks autonomously. Machine Learning’s aim is to help machines learn from data and make predictions and decisions. Data Science just aims to extract meaningful insights from data to inform decision-making and solve business-related problems.
How are AI, Machine Learning, and Data Science Related?
AI is a broad field trying to mimic human intelligence and enable computers to perform tasks autonomously. In doing so, it is creating intelligent machines. Machine Learning is a subset of AI that enables machines to learn from data using algorithms. It is one of five approaches that AI encompasses.
Data Science utilizes Machine Learning, as well as other tools and techniques, to extract valuable insights and information from complex data sets. In other words, Machine Learning is the in-between thread that connects AI and Data Science.
While Data Science and Artificial Intelligence are broader concepts, Machine Learning is a specific approach within AI that allows studying and extracting data, while being utilized by Data Science.
Careers in Machine Learning vs Data Science vs Artificial Intelligence
While all three fields of study are interconnected, each of them have distinct areas of focus. Here are the career path in each of these fields:
Data Science – Data Analyst, Data Scientist, Business Intelligence Analyst, Data Science Manager, Data Architect, etc.
Artificial Intelligence – AI Engineer, AI Researcher, Robotics Specialist, Natural Language Processing Engineer, Research Scientist, Computer Vision Specialist, etc.
Machine Learning – Machine Learning Engineer, AI Engineer, Data Scientist with a focus on Machine Learning, Computational Linguist, etc.
Salaries and Job Market Overview
As of 2025, all three fields of AI, Data Science, and Machine Learning are seeing a huge demand in jobs. There is a very high demand for professionals in each of these fields of work. Salaries can range anywhere from INR 4 LPA to 8 LPA for fresher in either of these fields, to INR 20 LPA to 40 LPA for experienced professionals. This is subject to their education backgrounds, their college, their company size and reputation, and the knowledge and skill set they acquire along the way.
For AI Engineers and other professionals in AI, salary can range anywhere from INR 5 LPA to 12 LPA for a fresher. With experience, somewhere around the mid-level, they can earn between INR 12 LPA and INR 20 LPA. Once they attain a senior level i.e. more than 5-6 years of experience, they can earn somewhere around INR 20 LPA and 40 LPA.
For Machine Learning Engineers, the average salary is around INR 11 LPA. It goes up with experience and may reach up to INR 15 LPA.
As for Data Scientists, the average salary is around INR 11 LPA to 12 LPA. However, not unlike AI, their salaries may also rise upwards to up to INR 30 LPA to 40 LPA with experience.
There is a huge demand for AI and Machine Learning experts, and it is only growing with time. In the upcoming years, a 40% uptick is expected in the demand for professionals in these fields of work. Jobs may go up to 1 million in AI and ML. Every single industry is now adopting AI, and therefore, it is soon going to be a necessary course to study in every field.
As for Data Scientists, Data Analysts, and Machine Learning experts, there is currently a shortage of skilled professionals, enough to fill every gap in an organization. However, this creates a unique opportunity for experts in the market.
As far as emerging technologies are concerned, Apache Spark, Databricks, and Snowflake are becoming increasingly important in Machine Learning Operations.
Benefits of Data Science and AI Course: Earn Your MBA Degree at MBA ESG College
Data Science and Artificial Intelligence is possibly one of the most, if not the most, in-demand jobs in the technological sphere right now. Besides its sense of accomplishments, the salaries are usually high enough from the beginning in this work for anybody to immediately start pursuing Data Science and Artificial Intelligence.
More importantly, due to the impactful nature of Data Science & AI and its penetrability in every field, employees working with Data Science will feel like they have made a difference. AI in particular is being employed in literally every single field of work. Therefore, soon enough, it is going to be a necessary course to learn for every individual.
Pursuing a career in this field of study may create multiple job opportunities – Data Scientist, Data Analyst, AI Engineer, Data Architect, NLP Engineer, Robotics Specialist, etc. Each of these career paths have tremendous growth opportunities. Any employee may start with a salary of INR 4 LPA and can earn up to INR 40 LPA or more in 5-6 years’ time.
Besides huge earning potential and a variety of career opportunities, a Data Scientist will also work with cutting-edge technologies. There is a rising demand for even specialized professionals in this field of work. Lastly, the continual rise of AI will also heavily tilt the favor towards Data Science in the future.
To pursue Data Science and Artificial Intelligence from a reputable college such as MBA ESG, one needs to pass with a 50% marks throughout their academics till bachelor’s degree.
MBA ESG provides one of the most on-brand education courses for Data Science & Artificial Intelligence, replete with industry experts who teach students based on what is expected out of them once they join the corporate world. The curriculum is designed in a way to cater to industry needs. This way, once the students join a company of their choice, they won’t feel at sea learning new things about their job. It helps in bridging the gap between college and corporate and sets them off on a bright and illustrious career path.
MBA ESG is also one of the top 20 MBA colleges in Europe and top 4 in Paris. It is one of the most rising colleges in India, with campuses in Bengaluru and Pune.
Frequently Asked Questions (FAQs)
1. Which is better: Data Science, AI, or Machine Learning?
While Machine Learning is a subset of AI, Data Science and AI are broader, bigger fields. Therefore, any job in the AI or Data Science space will be significantly bigger and more lucrative. Having said that, a job in Machine Learning will also be a decent enough job.
2. Which programming languages are used in AI, ML, and Data Science?
Python, R, and SQL, are some of the most commonly used programming languages in AI, ML, and data Science.
3. Is AI or Machine Learning a part of Data Science?
No. Machine Learning is a subset of AI, whereas Data Science utilizes both AI and Machine Learning to extract information from large data sets. AI helps in the simulation part of learning, thinking, and problem-solving, whereas Machine Learning focuses on algorithms to make data-driven decisions and helps computers to learn from the data without programming.
4. Do AI, Machine Learning, and Data Science require coding?
Yes, AI, Machine Learning, and Data Science require coding.
5. What skills are needed for a career in AI, Machine Learning, and Data Science?
Programming languages like R, Python R, SQl, as well as other areas like Deep Learning, Natural Language Processing, Statistical Analysis, Mathematics, Data Visualizations, Problem Solving, and Communication are some of the essential skills needed for a career in AI, Machine Learning, and Data Science.
6. Can I switch from Data Science to Machine Learning or AI?
Given that these fields are interconnected, yes, you can switch from Data Science to Machine Learning to AI.
